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Python implementation of Epsilon constraint augmented 1 & 2 for Multi Objective Decision Making

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amirhosss/EpsilonConstraint-Augmented-MODM-Python

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Getting Started

First we create an object from Augmented class and initialize "shape of problem", "steps" and "primary object".

augmented = Augmented(shape=shape, step=step, primary_obj=primary_obj)

Input data

Then we should initialize Constraint coefficients, Objective coefficients and Constraint values.

augmented.cons_coefficients = cons_matrix
augmented.obj_coefficients = obj_matrix
augmented.cons_values = cons_val_matrix

Run

Finally after declaring all variables and initializing model data, we use run method as follows:

augmented.run(output=False, version='v1')

It takes 2 arguments "output" and "version". Augmented version (v1, v2) specified by version and X array specified by output.

PLot

Plotting objectives by their order.

augmented.plot_objectives((objective_ord, objective_ord))

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Python implementation of Epsilon constraint augmented 1 & 2 for Multi Objective Decision Making

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